SAS business intelligence has analytical capabilities like statistics, reporting, data mining, predictions, forecasting and optimization. They help in getting data in the format desired. It helps in improving quality of data.

SAS BI provides the information about an enterprise when needed. It provides this information in customized format. SAS BI integrates data across the enterprise and delivers the self-service reporting and analysis. This consumes less time for responding requests and for business uses to view the information. An integrated, flexible and robust presentation layer for SAS Analytics with full breadth is also offered by SAS BI. All these are integrated within the context of business for better and faster decision making.

As name suggests it’s the Intelligence one gains from the business; about the business. Typically, it is achieved by various Data warehousing, Data mining and reporting tools and techniques.

These tools and techniques help the system to provide right information to right people at right time and right format. So, decision makers can more concentrate on their business of making decisions instead of wasting time in digging plies of enterprise data.

SAS has developed end to end business intelligence solution named as SAS Enterprise Intelligence Platform. It enables the users to extract and transform enterprise wide data into fully integrated reporting warehouse, leading to more usable business data and more effective decision making.

With the way; the platform is structured and the way metadata (The metadata is explored in details at the below sections) is handled; it becomes feasible to represent the single version of truth to the intended users.

SAS stores the data only once which and shares its metadata across all the applications dealing with that data which might be ETL tool trying to update that data or data mining tool trying to dig out that data for some ad-hoc queries or might be reporting tool producing monthly report for the business.

Metadata is often referred as “data about data”; but I would like to say it as it is nothing but additional information of your data.

Usually many applications which deal with the DATA need some basic information about it from their perspective; for example, a database system where you are going to save the data needs to know how user wants the data to be saved? So, when you fire a create table command on the database is nothing but you give that information to the database system. In more specific term you define the table structure which is gets recognized as tables Metadata.

In another example when some reporting application needs to produce the weekly report it needs the information about the fields on the report, format of those fields which are going to be represented to the user; what all database tables it’s going to deal with; in which library or schema they are located etc. etc. All those terms are referring nothing other than metadata.

So, it is same with SAS as well; In the context of SAS; metadata is the information about all the resources used in the provision of BI. The name of the column rather than the actual values stored within it. Information about How to read in data from non-SAS location. Description of report content rather than the actual report itself. Details of the access rights of all users. A description of the source and target tables used in data integration jobs; as well as details of all the transformations.

It is the location where all this metadata is saved in some specific format. SAS stores its metadata in centralised repository; which in turn is managed by SAS Metadata Server. This metadata is then shared with all the applications under SAS Open Metadata Architecture. This helps SAS in achieving single storage of data and consistency of the information among all the applications using it.

It is platform designed for Business intelligence solution. It has got different parts or tiers. The metadata sits alongside these tiers and works as glue to stick all these layers together. There are 4 different tiers; Data tier, Server tier, Client and Web tier.

All tiers can have been installed on the same machine or might be on different machines; however, it is common practise to have server tier and web tier on one machine and data tier and client tier on different machines.

Data tier – Is nothing but where the all Enterprise level data resides.

Server Tier – This includes all different types of SAS Servers. SAS Servers are similar to windows servers; which run in the background to serve the requests rose from client.

SAS servers are usually installed on different machines. Various SAS servers all listed as below;

SAS Workspace Server – The SAS Code generated by various client applications is sent to this server for execution. SAS Workspace server then access various datasets and libraries included in the code and executes them providing the output back to the end users. Each user has individual process allocated on the server.

SAS Stored Process Server – This is place where all SAS Stored Process are executed. SAS stored processes are centrally stored SAS programs that can be accessed from different SAS client and web applications.

Object Spawner – Its part of Server tier which is responsible for start-up of SAS Work space server and connect them with the Metadata Server.

SAS OLAP Server – This is used to access previously created OLAP cubes. It can read the cubes which have been created with other non-SAS applications. Process MDX queries. It is interesting to know that building the OLAP cubes is done by using SAS Workspace server while OLAP server can be used just for reading purpose.

SAS/Connect Server – It used to submit SAS code from one machine to be executed on another. Provides Remote Library Services, Data transfer services etc.

SAS/SHARE – Gives access to SAS files for multiple users at a time; and avoid connecting to the files thru different SAS/Connect remote logins.

Apart from this there are some additional SAS servers like Batch Server, Grid Server, Platform suit for SAS etc. However most important of all are SAS Workspace Server, SAS Stored Process Server, SAS OLAP server and Object Spwaner.

SAS business intelligence has analytical capabilities like statistics, reporting, data mining, predictions, forecasting and optimization. They help in getting data in the format desired. It helps in improving quality of data.

SAS BI provides the information about an enterprise when needed. It provides this information in customized format. SAS BI integrates data across the enterprise and delivers the self-service reporting and analysis. This consumes less time for responding requests and for business uses to view the information. An integrated, flexible and robust presentation layer for SAS Analytics with full breadth is also offered by SAS BI. All these are integrated within the context of business for better and faster decision making.

A business object can be used to represent entities of the business that are supported in the design. A business object can accommodate data and the behavior of the business associated with the entity. A business object can be any entity of the development environment or a real person, place or process. Business objects are most commonly used and can be used in businesses with volatile needs.

A broadcast agent allows automation of emails to be distributed. It allows reports to be sent to different business objects. It also users to choose the report format and send via SMS, fax, pagers etc. broadcast agents allow the flexibility to the users to receive reports periodically or not. They help to manage and schedule the documents.